The Agentic GTM Stack

AI sales agents that show their receipts

Two working sales agents, one shared attribution layer, and a methodology document you can hand to the most skeptical person in the room. Every action either agent takes logs as a touchpoint. Every touchpoint earns capped, conservative revenue credit. When someone asks what the AI actually produced, you open a SQL view and read them the number.

The question is coming

You are already spending on AI somewhere in the GTM motion. Drafting tools, enrichment tools, maybe an agent you wired up yourself one weekend. The spend is small, which is exactly why nobody has asked hard about it yet.

Somebody will. A co-founder. An investor. Your own discipline at the next planning conversation. The question sounds like “what did the AI actually earn,” and today the honest answer at most companies is a shrug. Every AI tool claims impact. Almost none can show it in a form a skeptic accepts.

This kit exists so you can answer with a number instead.

What it is

A self-deploy kit. You buy it, you deploy it, you own it. Three parts:

InboxCopilot reads your inbound email, qualifies leads against your criteria, and drafts replies. Every qualification and every draft logs as a touchpoint tied to a lead.

EnrichmentMessenger takes a CSV of prospects, enriches the rows it can verify, and writes first-touch messaging for net-new pipeline. A row with no email address never becomes a lead (a phantom lead would poison your cleanest number, so the adapter refuses it at the door).

The attribution layer runs under both. A Postgres schema and a set of SQL views that assign revenue credit by rules chosen to survive scrutiny: AI credit capped at 50% of any deal, no touchpoint counted twice, and assisted deals compared against unassisted deals so you can see the difference instead of asserting it.

The part most kits leave out

The schema is plumbing. A competent operator rebuilds it in a weekend, and this page tells you so on purpose. The weekend buys you the schema and nothing else. The two agents were verified against their own output contracts before anything shipped, and the discipline is written down in a methodology document that explains how credit is assigned, why the cap exists, how the cohorts are defined, and, in a section most vendors would delete, what these numbers cannot claim.

That document is the spine of the product. It is numbers built to survive a CFO, whether or not you have one yet. The spec behind this kit budgeted two to four weeks to build the whole thing properly. The weekend was the cheap part.

What the numbers will not claim

Read this before you buy, because it will not change after you buy.

Attribution measures. It does not prove causation. A touchpoint on a closed deal means the agent touched the deal, and the credit model assigns a capped, conservative share of that deal's revenue. It does not mean the deal closed because of the agent, and the methodology says so in writing. The views also carry a minimum-sample rule: when your deal count is too small for a cohort comparison to mean anything, the dashboard says so instead of pretending.

If you want a tool that promises lift, there are plenty. This one promises evidence.

Your afternoon

Deployment is real work and it is yours. Plan on an afternoon if you are the RevOps hire, or the operator wearing that hat: create a Supabase project, run three migrations, set your API keys, connect the inbox InboxCopilot rides, drop your first CSV into EnrichmentMessenger. The docs carry the whole path from purchase to your first attribution view, troubleshooting included, because nobody is coming to do it for you.

That last sentence is a feature. Nothing about this purchase puts a meeting on your calendar or mine. The kit assumes you can run provided SQL and manage API keys, and it says so here so the wrong buyer can leave now instead of after checkout.

Who should not buy this

Save yourself $349 if any of these are true:

• Nobody at your company has ever created a Supabase project. This is not your kit.
• You want a managed service, implementation help, or a calibration call. This is a kit. Nobody is coming.
• You need native Salesforce or HubSpot integration at purchase. The attribution layer is its own Postgres store; CRM sync is on the roadmap, and a roadmap is not a promise.
• You expect attribution to prove causation or guarantee lift. The product measures. It does not manufacture revenue.
• You have enterprise procurement, a security review, or SLA requirements. Wrong product, wrong company size, wrong price.

No case studies yet, on purpose

This product launches with no case studies, and I am not going to invent any. Its first proof will be its own attribution data, published as it accrues. A measurement product that borrowed someone else's numbers to sell itself would be confessing something. Watch the dashboard instead.

What you get

The full monorepo: both agent skills with their JSON output contracts, the attribution schema and views, service runners, deployment scaffolding, dashboards, and the docs (SETUP.md for the path, METHODOLOGY.md for the argument). Versioned, with updates published to the repo. No SLA, no support inbox, no maintenance contract. You own your deployment the day you clone it. If that sentence loses the sale, it was a bad-fit sale.

$349, one time

One price. No tiers, because there is nothing honest to subtract for a cheaper one. Stripe checkout, and the delivery email with your repo link arrives within minutes.

All sales are final once the delivery email sends. The repo is the product, and the product is delivered.

Buy the Agentic GTM Stack for $349

The question is coming. Buy the answer before someone asks.